In T358095#9661143, @praptijaduvanshi wrote:In T358095#9661010, @Mistura14 wrote:Please how do we go about recording the contribution and submitting a final application
You can go to project selection page on outreachy --> Find 'Wikimedia closed project #1' --> Record your contribution and apply.
We need to share the link to our notebook as a contribution. The link will be the similar to the link you shared for feedback.Please correct me if I'm wrong.
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Mar 27 2024
Mar 27 2024
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Mar 26 2024
Mar 26 2024
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Please how do we go about recording the contribution and submitting a final application
Mar 21 2024
Mar 21 2024
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9649415, @DevJames1 wrote:In T358095#9649341, @Mistura14 wrote:It is expected that in some date intervals, depending on the granularity used, the interval may be too tight to return any reasonable data. Therefore you can use a try-and-except block or similar techniques to handle such occurrences, and not terminate the execution.
Mar 20 2024
Mar 20 2024
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9644034, @Shruti799 wrote:
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9644718, @Kn138 wrote:Hi, are we allowed to manipulate the data for part 2? If I wanted to display page_lengths with granularity monthly, can I group page_lengths as an average for a given month? For example, a bar chart for page_lengths for 2021 with granularity monthly. X axis would be months and Y axis would be average page lengths for a given month.
Mar 18 2024
Mar 18 2024
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9637039, @Jane_Ngethe wrote:In T358095#9636935, @MahimaSinghal wrote:In T358095#9636917, @Jane_Ngethe wrote:Hi @Jane_Ngethe The error you are seeing is because the the size of your file has increased the server's file size limit.
OK. What can I do?
Mar 16 2024
Mar 16 2024
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9635564, @Ansha_Pashine wrote:Do we necessarily need to include the revision timestamps or pageview counts in our visualization?
It's not specified but we accessed the data for the pageview counts and this made me think over it
Mar 9 2024
Mar 9 2024
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9615283, @CMyrick-WMF wrote:Message from the project mentors: How will we judge applicants?
It's common for folks to ask us how to make a strong application for this project. The task is open-ended so there is no one "right" answer, but we'll try to give you a bit more guidance. The final notebook (created for the microtask) is our primary means of judging each applicant. For the notebook, we will evaluate it along a few criteria:
- Quality of code: are there bugs? is your code well-structured, commented, and easy to understand?
- Quality of notebook: is the notebook well-structured and easy to follow?
- Creativity: did you try different approaches? did you come up with interesting ideas for future analyses?
- Iteration: if you receive feedback, were you able to incorporate those changes?
NOTE: because we will likely only provide one round of feedback for each applicant, we recommend submitting the notebook when you are fairly confident it is a complete state. As noted above, you are not evaluated on the quality of your initial notebook but rather how you adapt to the feedback so it's okay to have mistakes, etc., in your notebook in the initial review and you will not be penalized for that.
Mistura14 added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
@MahimaSinghal Thanks for sharing the Notebook file. It realy helped.
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